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• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 商科代写|计量经济学代写Econometrics代考|STRUCTURAL BREAKS

So far, we have assumed that the parameters of the regression model are constants. However, this is an assumption which we may wish to test under certain circumstances. For example, suppose there is a significant change in the economic environment, such as a major banking crisis, the outbreak of war, or a disease pandemic. It would be sensible to test whether such events have an effect on the parameters of the models which we estimate. A number of tests exist which allow us to do this, and we will consider some of the more commonly used tests here.

Tests for structural breaks, or parameter instability, differ according to whether or not we are aware of the nature of the division of the sample prior to estimation. The easier case to deal with is when we can identify the sample division in advance. When using cross-section data, we might wish to divide the sample into different subgroups and test if the parameters are constant across these groups. For example, if we have a sample of hours worked and wages paid, we could partition the sample according to some broad characteristics, say male and female workers, and test if the elasticity of hours worked with respect to the wage is the same for both groups. When working with time-series data, we might be aware of the date at which a major event occurred, which is the potential cause of parameter instability. Hence, we would divide the sample into observations prior to, and after, this date and test if the parameters are the same across subperiods.

## 商科代写|计量经济学代写Econometrics代考|Binary Dependent Variables

Consider the standard regression model $Y_{i}=a+\beta X_{i}+u_{i}$. If we assume that the error follows a normal distribution, in which any real value is possible, then it follows that $Y_{i}$ should also be able to take on any real value. However, the data we deal are often not consistent with this. In many cases, the dependent variable can only take on a limited number of values. One common example of this is when it is binary in nature. An example of this is survey data in which individuals are asked if they are employed or unemployed. Alternatively, we might observe a sample of companies some of which go into liquidation during a given period and some of which do not. In both these cases, the data can be coded so that the variable to be explained takes on only two possible values $-0$ or 1 .

There is nothing to prevent us from calculating a least squares regression equation even if the variable to be explained is coded as a $0-1$ variable. However, the interpretation of such an equation becomes somewhat problematic. To illustrate this, let us consider a specific example. Suppose we have data for the share price of a company which is coded as 1 for days on which the share price rises, and 0 for days on which it remains constant or falls. We wish to examine whether there is a relationship between movements in the share price (coded in this way) and movements in the overall stock market index. As a first attempt, we estimate a least squares regression of the share price change variable (in our example, this is the price of British Airways (BA) shares) on a constant and the change in the Financial Times Stock Exchange (FTSE) market index. The results are given in equation (7.1),
\begin{aligned} &B A_{t}=\underset{(0.0121)}{0.4959}+\underset{(1.2499)}{23.3086} F T_{t}+u_{t} \ &R^{2}=0.2032 \quad D W=2.0407 . \end{aligned}

# 计量经济学代考

## 商科代写|计量经济学代写Econometrics代考|Binary Dependent Variables

$$B A_{t}=\underset{(0.0121)}{0.4959}+\underset{(1.2499)}{23.3086 T_{t}+u_{t}} \quad R^{2}=0.2032 \quad D W=2.0407 .$$

## 有限元方法代写

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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